Particle swarm optimization with active congregation

ICIC Express Letters

Volumn 4, Issue 4, 2010, Pages 1167-1172

  Cui, Zhihua ^a   Wang, Liang ^a   Tan, Ying ^a  

^a TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Active congregation; Active contribution index; Particle swarm optimization

Indexed keywords

ACTIVE CONGREGATION; EXPLORATION AND EXPLOITATION; MULTI-MODAL; NUMERICAL PROBLEMS; PASSIVE CONGREGATION; SIMULATION RESULT; VELOCITY UPDATE EQUATION;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 77955189827     PISSN: 1881803X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. J. Kennedy and R. C. Eberhart, Particle swarm optimization, Proc. of the IEEE International Conference on Neural Networks, Piscataway, NJ, pp.1942-1948, 1995.
2. R. C. Eberhart and J. Kennedy, A new optimizer using particle swarm theory, Proc. of the 6th International Symposium on Micro Machine and Human Science, Piscataway, NJ, pp.39-43, 1995.
3. S. Chen, X. Hong, B. L. Luk and C. J. Harris, Non-linear system identification using particle swarm optimisation tuned radial basis function models, International Journal of Bio-Inspired Computation, vol.1, no.1/2, pp.246-258, 2009.
4. A. M. Senthil, M. G. Ramana and C. K. Loo, On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms, International Journal of Bio-Inspired Computation, vol.1, no. 1/2, pp.198-209, 2009.
5. T. Cura, Particle swarm optimization approach to portfolio optimization, Nonlinear Analysis: Real World Applications, vol.10, pp.2396-2406, 2009.
6. K. E. Parsopoulos, F. Kariotou, G. Dassios and M. N. Vrahatis, Tackling magnetoencephalography with particle swarm optimization, International Journal of Bio-Inspired Computation, vol.1, no.1/2, pp.32-49, 2009.
7. C. K. Monson and K. D. Seppi KD, The Kalman swarm: A new approach to particle motion in swarm optimization', Proc. of the Genetic and Evolutionary Computation Conference, Piscataway, NJ, pp.140-150, 2004.
8. J. Sun J. et al., Particle swarm optimization with particles having quantum behavior', Proc. of the IEEE Congress on Evolutionary Computation, Piscataway, NJ, pp.325-331, 2004.
9. Z. H. Cui and J. C. Zeng, A guaranteed global convergence particle swarm optimizer, Lecture Notes in Artificial Intelligence, vol.3066, Sweden, Springer, pp.762-767, 2004.
10. Z. H. Cui, X. J. Cai, J. C. Zeng and G. J. Sun, Particle swarm optimization with FUSS and RWS for high dimensional functions, Applied Mathematics and Computation, vol.205, pp.98-108, 2005.
11. Z. H. Cui, J. C. Zeng and G. J. Sun, A fast particle swarm optimization, International Journal of Innovative Computing, Information and Control, vol.2, no.6, pp.1365-1380, 2006.
12. X. J. Cai, Z. H. Cui, J. C. Zeng and Y. Tan, Performance-dependent adaptive particle swarm optimization, International Journal of Innovative Computing, Information and Control, vol.3, no.6(B), pp.1697-1706, 2007.
13. X. J. Cai, Z. H. Cui, J. C. Zeng and Y. Tan, Particle swarm optimization with self-adjusting cognitive selection strategy, International Journal of Innovative Computing, Information and Control, vol.4, no.4, pp.943-952, 2008.
14. S. He, Q. H. Wu et al., A particle swarm optimizer with passive congregation, BioSystems, vol.78, pp.135-147, 2004.
15. H. K. Parrish and W. M. Hamner, Animal Groups in Three Dimensions, Cambridge University Press, 1997.
16. X. Yao, Y. Liu and G. M. Lin, Evolutionary programming made faster, IEEE Transactions on Evolutionary Computation, 1999, vol.3, no.2, pp.82-102.
17. A. Ratnaweera, S. K. Halgamuge and H. C. Watson, Self-organizing hierarchical particle swarm opitmizer with time-varying acceleration coefficients, IEEE Transactions on Evolutionary Computation, vol.8, no.3, pp.240-255, 2004.